Examinando por Materia "Indexes"
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- PublicaciónSólo datosImplications of Very Deep Super-Resolution (VDSR) on RGB imagery for grain yield assessment in wheat(2020 Virtual Symposium in Plant Omics Sciences, OMICAS 2020, 2021-09-13) Fernandez-Gallego, Jose A.; Kefauver, Shawn C.; Gutiérrez, Nieves A.RGB imagery has been widely used for crop management practices and phenotyping applications in recent years. Although RGB wavelengths (400-700 nm) are not able to capture all essential plant data (such as with full ultraviolet, near and long infrared wavelength coverage), RGB cameras are the most common types of cameras and are among the versatile imaging devices for proximal remote sensing applications. Deep learning strategies have improved a wide range of processes and deep learning concepts can be included in many applications. This work uses the Very Deep Super-Resolution (VDSP) technique to improve low-resolution RGB images in order to study grain yield assessment in wheat using vegetation indexes. The results show no significant differences between indexes calculated from low-resolution images and low-resolution images processed using VDSP with grain yield.
- PublicaciónSólo datosOpen-Source Software for Crop Physiological Assessments Using High Resolution RGB Images(International Geoscience and Remote Sensing Symposium (IGARSS), 2021-02-17) Kefauver, Shawn C.; Romero, Adrian Gracia; Buchaillot, Ma. Luisa; Vergara-Díaz, Omar; Fernandez-Gallego, Jose A.; El-Haddad, Georges; Akl, Alexi; Araus, José LuísThe state-of-the-art on the use of commercially available consumer color digital cameras, which capture Red, Green and Blue light covering the visible spectrum with broad spectral bands but at high spatial resolution and with accurate color calibration has produced some interesting results in recent years, bringing back the benefits of “hyperspatial” imaging for estimating various plant physiological characteristics related to both biotic and abiotic stressors. Here we will review various RGB vegetation indexes that use the spectral concept for the estimation of biomass and canopy chlorophyll, the Normalized Green Red Difference Index (NGRDI) and the Triangular Greenness Index (TGI), as well as others that are in popular use based on this same concept as more traditional style vegetation indices often used with multispectral data. We will also introduce spectral indexes based on alternate color space transforms such as Hue Saturation Intensity (HSI), CIE-Lab and CIE-Luv and their practical calculations. Practical aspects of the calculation of these RGB vegetation indexes are offered using open-source software plugins for FIJI (FIJI is Just ImageJ), including the MaizeScanner, CerealScanner, and their mobile-to-cloud ODK (Open Data Kit) versions Fusion and CerealsFusion.